1. Field of the Invention
The invention pertains to the detection of respiratory insufficiency in the breathing of a subject, and the generation of an artificial neural network for use in such detection.
2. Description of the Related Art
The technique of monitoring capnogram samples of gas at or near the airway of a non-intubated subject to detect respiratory insufficiency in the breathing of the subject is known. Generally, this technique relies on the fluctuation of CO2 present in the airway of the subject as the subject inhales (reducing CO2 levels) and exhales (increasing CO2 levels). However, this technique has a drawback in that there are various circumstances in which the subject is not breathing, or not breathing sufficiently, that may not be detected by conventional systems implementing this technique.
For example, the subject may make attempts at breathing without moving sufficient volume of gas into and out of the lungs. These small, un-productive breaths can be caused by over-sedation or by airway obstruction, among other things. Unfortunately, simple capnometry may not be capable of discerning these small, inadequate breaths from safe tidal breathing. As another example, cardiogenic oscillations are a phenomenon in which the beating of the heart causes very small movements of gas into and out of the lungs. While these movements of gas may be detected by conventional systems as sufficient respiration, the amount of gas moved will not be enough to sustain the subject.